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Combining the intelligent algorithm such as BP neural network and support vector maching (SVM) with traditional chemical method, this paper models the relationship between plant surface color and its pigment. Using the neural network model constructed above, people can figure out the content of plant pigments by getting the corresponding plant surface color information. Compared with the traditional...
Improving quality of noisy images has been an active area of research in many years. It has been shown that wavelet thresholding methods had better results than classic approaches. However estimation of threshold and selection of thresholding function are still the challenging tasks. In this paper, a new thresholding function is proposed for wavelet thresholding. This function is continues and has...
For celestial spectra are vectors in a several-thousand-dimensional space with a mass of redundancy and usually contaminated with various noises, feature extraction is an essential procedure in automatic spectra processing. We investigated the feature extraction problem for Quasar and Galaxy spectra classification. The available methods in literature can be loosely classified into the following types:...
The goal of this project is thus to experiment with ANNs and to evaluate performance of ANN models in studying stock price patterns in time by attempting to predict future results of a time-series by simply studying patterns in the time-series of stock prices. In this project we have instantiated the proposed Neural Network using the stock prices of Iran Tractor Manufacturing Company during two years...
This study proposed to use wavelet transfer to acquire image features, and use back-propagation neural network to classify type of textile texture. Firstly, wavelet transfer is applied to obtain vertical, horizontal and diagonal images of original image, and compute its wavelet energy to take them as texture features of this image. Finally, the back-propagation neural network is adopted to recognize...
The increasingly rapid advances in technology development, approaches to integrate the property market valuation with Geographical Information System (GIS). Application of GIS in Property Valuation field very helpful for property market valuation information to presented in map and table using ArcGIS 9.3 software. It purpose is to facilities the access and searching the information. Before this, information...
This paper presents a new approach for power system fault classification based on principal component analysis (PCA) and probabilistic neural network (PNN).the work presented in this paper is focused on identification of simple power system faults. The new model mainly includes three steps. Firstly wavelet transform is used to analyze power system fault signals, and distinguishing features are extracted...
This paper focused on experimental data and study for the testing of the material mechanical properties using vibration technique. By applying vibration analysis and testing on the material, we could determine the natural frequencies, the damping ratio and mode shapes of the structure. However, in this study, we only considering the natural frequencies of the material as the input data needed for...
The aim of this research is to develop an intelligent automated online forecasting of a car fuel consumption using neural network and classified it into classes of driving style. A new online monitoring tool was developed to acquire and analyze data collected from a car for the purpose of fuel consumption modelling and forecasting. The data was transmitted via ECU Can Bus attach to the car to the...
This manuscript describes a methodology to design a controller for an artificial muscles type four fingers dexterous robotics hand. Electro-Active Polymers (EAP)materials have been used to construct the muscles type four fingers hand. The main dilemma in the control of artificial muscles type fingers, is to provide an accurate fingertips tracking within the operational space. Yet, if bending angles...
In this paper, an efficient scheme to detect the unprecedented changes in system reliability and find the failed component state by classifying the faults is proposed using kalman filter and hybrid neuro-fuzzy computing techniques. A fault is detected whenever the moving average of the Kalman filter residual exceeds a threshold value. The fault classification has been made effective by implementing...
Hot Carrier Degraded(HCD), Electro-Static discharge(ESD) and Time-Dependent Dielectric Breakdown (TDDB) are the main failure modes of electronic devices. Identifying degraded state of electronic devices needs considering the combined effects of various factors. In this paper, On the basis of information such as real-time HCD damage, ESD damage, etc were obtained, with the help of fuzzy integral, which...
For the reasons of low fault diagnosis accuracy of traditional diagnosis methods, a fault diagnosis method fusing BP neural Network and multi-sensor information fusion technique based on D-S evidence theory was presented to realize fault diagnosis. On the base of integrated neural network, importing evidential reasoning, a fault diagnosis technique which combine neural network and D-S evidential reasoning...
There are some shortages of knowledge acquisition and inefficency in ES. So, combines ES with ANN to construst military equipment fault diagosis expert system. Introduces the neural network learning system, the knowledge base and the reasoning mechanism of the expert system. After introducing ANN and ES, utilizing the adapting, self-learning abilities of ANN, methods of knowledge acquirement and representation...
This paper presents three intelligent methods for condition monitoring of induction motors in real-time. A structured neural network has been designed to prognosis of instantaneous faults. The inputs of neural network are the standard deviation and mean of feature signal obtained by Hilbert transform of one phase current signal. The stator related faults have been diagnosed by designing fuzzy logic...
Automatic Number Plate Recognition (ANPR) is a real time embedded system which identifies the characters directly from the image of the license plate. It is an active area of research. ANPR systems are very useful to the law enforcement agencies as the need for Radio Frequency Identification tags and similar equipments are minimized. Since number plate guidelines are not strictly practiced everywhere,...
Aiming at the difficulty of tank unit combat formation recognition in virtual simulation training, the recognition method based on BP neural network is put forward. After analyzing the definition and character of the tank unit combat formation, the recognition strategy for tank unit formation is put forward. Then the recognition model based on BP neural network is built. In order to get plentiful...
Effective complex permittivity measurements of materials are important in microwave engineering and microwave chemistry. Artificial neural network (ANN) computational module has been used in microwave technology and becomes a useful tool recently. A neural network can be trained to learn the behavior of an effective complex permittivity of material under microwave irradiation in a test system and...
Due to different levels and characteristic deformation existing in any images, it is difficult to select an appropriate model to correct effectively. Considering BP neural network is a high and nonlinear complicated system which can approach at any precision, we attempt to use it for image geometric correction. In this paper, errors correction of scanning map by BP neural network as an example was...
Fault diagnosis of transformer in power system is studied in this paper. Considering the excellent performances of Random Forest (RF) in pattern recognition, we apply RF to construct a diagnosis model to predict the situation of transformer. The experiments of fault diagnosis for some real transformers show that RF obtains a better result in prediction accuracy and stability than traditional Back...
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